{"id":"W2131256161","doi":"10.1109/aps.2006.1710813","title":"Frequency Dispersion Effects on FDTD Model for Breast Tumor Imaging Application","year":2006,"lang":"en","type":"article","venue":"2006 IEEE Antennas and Propagation Society International Symposium","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Finite-difference time-domain method; Debye; Dispersion (optics); Lorentz transformation; Computer science; Debye model; Time domain; Algorithm; Frequency domain; Applied mathematics; Physics; Computational physics; Mathematics; Mathematical analysis; Optics; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002474772,0.0003446874,0.0002750616,0.000343758,0.0002669254,0.0004715022,0.0005791476,0.001022909,0.001556657],"category_scores_gemma":[0.001455874,0.0002239382,0.0003553849,0.0005094247,0.0002385008,0.0005836639,0.0003007915,0.0005883499,0.0009636686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005595469,"about_ca_system_score_gemma":0.0003807157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003037408,"about_ca_topic_score_gemma":0.001933076,"domain_scores_codex":[0.9998198,0.00003399419,0.000008730063,0.00002542708,0.00009881515,0.0000132427],"domain_scores_gemma":[0.9996759,0.0001781868,0.00002716849,0.00003207388,0.00007997489,0.00000674582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001442282,0.00003636474,0.001085035,0.0002045568,0.00001726204,0.0005852986,0.0003680338,0.8229641,0.05125711,0.04453297,0.004675497,0.07412945],"study_design_scores_gemma":[0.000002377954,0.000009265609,0.00009923873,0.00001074935,0.000005334332,0.000145162,0.00001058608,0.9885798,0.004281667,0.001912205,0.004937402,0.000006258153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01610029,0.0008774978,0.9745646,0.0002802676,0.0001317673,0.00002234859,0.00008115068,0.0004013189,0.007540789],"genre_scores_gemma":[0.634437,0.00430487,0.3284243,0.0003472851,0.0001688542,0.0002073223,0.0004380386,0.0005318515,0.03114045],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003037408,"threshold_uncertainty_score":0.006039441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003534694048197284,"score_gpt":0.2025408743242457,"score_spread":0.1990061802760484,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}